Chipotle Mexican Grill (CMG) EV to EBITDA (2009 - 2026)
Chipotle Mexican Grill's (CMG) quarterly EV to EBITDA came in at 80.57 in Q2 2026, down 38.92% year-over-year from 131.91 in Q2 2025, and down 20.4% quarter-over-quarter from 101.22 in Q1 2026.
Chipotle Mexican Grill (CMG) EV to EBITDA (2009 - 2026) Analysis & Trends
Chipotle Mexican Grill (CMG) has reported EV to EBITDA for 18 consecutive years, with 80.57 the latest figure, recorded in Q2 2026.
- On a quarterly basis, EV to EBITDA fell 38.92% year-over-year to 80.57 in Q2 2026; TTM through Jun 2026 was 23.27, a 39.2% decrease from a year earlier, with the FY2025 full-year figure at 24.35, down 41.89% from the prior year.
- EV to EBITDA was 80.57 for Q2 2026 at Chipotle Mexican Grill, down from 101.22 in the prior quarter.
- Over five years, EV to EBITDA peaked at 228.72 in Q1 2022 and troughed at 80.57 in Q2 2026.
- A 5-year average of 137.82 and a median of 129.1 in 2022 frame the typical range for EV to EBITDA.
- Across the five-year window, EV to EBITDA plunged 58.29% in 2022 and jumped 41.79% in 2024, its largest moves.
- Over 5 years, EV to EBITDA stood at 126.3 in 2022, then soared by 33.8% to 168.98 in 2023, then rose by 14.31% to 193.16 in 2024, then plunged by 41.94% to 112.15 in 2025, then dropped by 28.16% to 80.57 in 2026.
- The last three EV to EBITDA figures came in at 80.57 (Q2 2026), 101.22 (Q1 2026), and 112.15 (Q4 2025), per Business Quant data.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 168.67 Bn | 167.85 Bn | 6.42 Bn |
| 2 | Starbucks | 107.32 Bn | 103.72 Bn | 6.49 Bn |
| 3 | Chipotle Mexican Grill | 41.40 Bn | 40.73 Bn | 2.35 Bn |
| 4 | Yum Brands | 38.39 Bn | 37.72 Bn | 1.47 Bn |
| 5 | Restaurant Brands International | 25.02 Bn | 25.51 Bn | 1.89 Bn |
| 6 | Darden Restaurants | 24.39 Bn | 24.17 Bn | 3.68 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 15.95 Bn | 1.89 Bn |
| 8 | Yum China Holdings | 14.09 Bn | 13.41 Bn | 2.22 Bn |
| 9 | Texas Roadhouse | 10.81 Bn | 10.63 Bn | 1.44 Bn |
| 10 | Dominos Pizza | 9.81 Bn | 9.60 Bn | 478.23 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 80.57 |
| Mar 31, 2026 | 101.22 |
| Dec 31, 2025 | 112.15 |
| Sep 30, 2025 | 105.62 |
| Jun 30, 2025 | 131.91 |
| Mar 31, 2025 | 138.21 |
| Dec 31, 2024 | 193.16 |
| Sep 30, 2024 | 163.01 |
| Jun 30, 2024 | 143.86 |
| Mar 31, 2024 | 177.72 |
| Dec 31, 2023 | 168.98 |
| Sep 30, 2023 | 123.62 |
| Jun 30, 2023 | 133.52 |
| Mar 31, 2023 | 125.34 |
| Dec 31, 2022 | 126.30 |
| Sep 30, 2022 | 121.58 |
| Jun 30, 2022 | 105.28 |
| Mar 31, 2022 | 228.72 |
| Dec 31, 2021 | 302.83 |
| Sep 30, 2021 | 209.08 |
Chipotle Mexican Grill EV to EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=CMG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "CMG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=CMG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();